With the emergence of the COVID-19 pandemic, virtual simulation games have provided an effective teaching method for online entrepreneurship education. By exploring the mechanisms that influence student engagement and learning outcomes from different perspectives, such as game design, team and individual perspectives, numerous scholars have demonstrated that such a teaching method can effectively improve students’ engagement and learning performance. However, the existing studies are relatively scattered, and there is a scarcity of studies in which the effects of said (...) factors are considered. Based on the learning process 3P model proposed by Biggs, students’ perceived experience of game design, teamwork and self-efficacy were taken as variables in the early learning stage in the present study, and the influence mechanism of virtual simulation game learning experience on students’ engagement and entrepreneurial skill development was explored, so as to close the gap in existing research. In the present study, 177 college students from Chinese universities were surveyed and the data were surveyed using AMOS 23.0 software. Although the empirical results show that students’ “goal and feedback” and “alternative” experience of game design did not have a significant positive impact on students’ engagement, there was a direct and significant effect the development of entrepreneurial skills. Students’ experience of teamwork and general self-efficacy could not only directly and significantly affect the development of entrepreneurial skills, but also indirectly affect the development of entrepreneurial skills through learning engagement. The research results are practically significant for teachers in the selection and development of virtual simulation games, can be effectively applied in teaching process management, and can improve students’ engagement and learning performance. (shrink)

Students in an undergraduate legal and ethical issues course continually told the authors that they did not have time to study for the course because they were busy studying for their clinical courses. Faculty became concerned that students were failing to realize the value of legal and ethical concepts as applicable to clinical practice. This led the authors to implement a transformational learning experience in which students applied legal and ethical course content in a high-fidelity human simulation (HFHS) scenario. (...) A preliminary evaluation compared the new HFHS experience with in-person and online student groups using the same case. Based on both student and faculty perceptions, the HFHS was identified as the best of the three approaches for providing a transformational learning experience regarding legal and ethical content. (shrink)

How do speakers learn the social meaning of different linguistic variants, and what factors influence how likely a particular social–linguistic association is to be learned? It has been argued that the social meaning of more salient variants should be learned faster, and that learners' pre‐existing experience of a variant will influence its salience. In this paper, we report two artificial‐language‐learning experiments investigating this. Each experiment involved two language‐learning stages followed by a test. The first stage introduced the artificial (...) language and trained participants in it, while the second stage added a simple social context using images of cartoon aliens. The first learning stage was intended to establish participants' experience with the artificial language in general and with the distribution of linguistic variants in particular. The second stage, in which linguistic stimuli were accompanied by images of particular aliens, was intended to simulate the acquisition of linguistic variants in a social context. In our first experiment, we manipulated whether a particular linguistic variant, associated with one species of alien in the second learning phase, had been encountered in the first learning phase. In the second experiment, we manipulated whether the variant had been encountered in the same grammatical context. In both cases we predicted that the unexpectedness of a new variant or a new grammatical context for an old variant would increase the variant's salience and facilitate the learning of its social meaning. This is what we found, although in the second experiment, the effect was driven by better learners. Our results suggest that unexpectedness increases the salience of variants and makes their social distribution easier to learn, deepening our understanding of the role of individual language experience in the acquisition of sociolinguistic meaning. (shrink)

We argue that modern approaches to teaching Corporate Social Responsibility rely heavily on abstract descriptions of poorly framed problems. Such problems often point to a reality that does not favour the development of CSR. Instead it creates a level of abstraction between “business” and “social responsibility” because there is no real experience of the challenges of integrating CSR into business practice. The number one challenge of making CSR work is integrating it into culture and business practices. To assist in helping (...) the future leaders of tomorrow understand their studies, we propose that a deeper integration between theory and practice is important. In this paper it is argued that this deeper integration can be achieved using small simulations in which students attempt to integrate CSR into real world situations and reflect on this experience. The reflection enables them to capture insights that are often absent from abstractions such as case studies. We offer an action research study to demonstrate how this reflective cycle works in two separate courses where this approach was applied. From this, these lessons are developed into a discussion where future directions are discussed. (shrink)

This research explores the application of an innovative learning approach by using trading simulation tutorials to reinforce the conventional learning styles in a corporate finance subject at postgraduate level. The majority of surveyed students perceive that their learning experience has been significantly enhanced through simulated trading tutorials. The post-trading survey shows students also indicate feeling more confident to self-monitor their learning. Furthermore, themajority of students feel able to recognise ethical issues in relation to trading in (...) securities. This research highlights some potentially negative effects if trading simulations were to be used in isolation without providing students with a solid background in ethics. This issue is even more relevant in the post Global Financial Crisis environment. If carefully designed and implemented, trading simulations have a potential to mitigate some potentially negative effects of the use of technology and be an effective and inclusive teaching tool. (shrink)

This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of (...) dispute over the epistemic superiority thesis have assumed. The superiority depends on features of the question and on a property of natural kinds that has been mistaken for material similarity. Seeing this requires holding other things equal in the comparison of the two methods, thereby exposing that, under the conditions that will be specified, the simulation is necessarily epistemically one step behind the corresponding experiment. Practical constraints like feasibility and morality mean that scientists do not often face an other-things- equal comparison when they choose between experiment and simulation. Nevertheless, I argue, awareness of this superiority and of the general distinction between experiment and simulation is important for maintaining motivation to seek answers to new questions. (shrink)

This paper defends the naïve thesis that the method of experiment has per se an epistemic superiority over the method of computer simulation, a view that has been rejected by some philosophers writing about simulation, and whose grounds have been hard to pin down by its defenders. I further argue that this superiority does not come from the experiment’s object being materially similar to the target in the world that the investigator is trying to learn about, as both sides of (...) dispute over the epistemic superiority thesis have assumed. The superiority depends on features of the question and on a property of natural kinds that has been mistaken for material similarity. Seeing this requires holding other things equal in the comparison of the two methods, thereby exposing that, under the conditions that will be specified, the simulation is necessarily epistemically one step behind the corresponding experiment. Practical constraints like feasibility and morality mean that scientists do not often face an other-things- equal comparison when they choose between experiment and simulation. Nevertheless, I argue, awareness of this superiority and of the general distinction between experiment and simulation is important for maintaining motivation to seek answers to new questions. (shrink)

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.g., gendered suffixes). Given that numerous systems for marking grammatical categories exist in natural languages, it follows that a better understanding of these findings can shed light on the factors underlying this diversity. In two discriminative learning simulations and an artificial language (...) learning experiment, we identify two factors that modulate linear order effects in linguistic category learning: category structure and the level of abstraction in a category hierarchy. Regarding category structure, we find that postmarking brings an advantage for learning category diagnostic stimulus dimensions, an effect not present when categories are non‐confusable. Regarding levels of abstraction, we find that premarking of super‐ordinate categories (e.g., noun class) facilitates learning of subordinate categories (e.g., nouns). We present detailed simulations using a plausible candidate mechanism for the observed effects, along with a comprehensive analysis of linear order effects within an expectation‐based account of learning. Our findings indicate that linguistic category learning is differentially guided by pre‐ and postmarking, and that the influence of each is modulated by the specific characteristics of a given category system. (shrink)

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.g., gendered suffixes). Given that numerous systems for marking grammatical categories exist in natural languages, it follows that a better understanding of these findings can shed light on the factors underlying this diversity. In two discriminative learning simulations and an artificial language (...) learning experiment, we identify two factors that modulate linear order effects in linguistic category learning: category structure and the level of abstraction in a category hierarchy. Regarding category structure, we find that postmarking brings an advantage for learning category diagnostic stimulus dimensions, an effect not present when categories are non‐confusable. Regarding levels of abstraction, we find that premarking of super‐ordinate categories (e.g., noun class) facilitates learning of subordinate categories (e.g., nouns). We present detailed simulations using a plausible candidate mechanism for the observed effects, along with a comprehensive analysis of linear order effects within an expectation‐based account of learning. Our findings indicate that linguistic category learning is differentially guided by pre‐ and postmarking, and that the influence of each is modulated by the specific characteristics of a given category system. (shrink)

Recent laboratory experiments have shown that both infant and adult learners can acquire word‐referent mappings using cross‐situational statistics. The vast majority of the work on this topic has used unfamiliar objects presented on neutral backgrounds as the visual contexts for word learning. However, these laboratory contexts are much different than the real‐world contexts in which learning occurs. Thus, the feasibility of generalizing cross‐situational learning beyond the laboratory is in question. Adapting the Human Simulation Paradigm, we conducted a (...) series of experiments examining cross‐situational learning from children's egocentric videos captured during naturalistic play. Focusing on individually ambiguous naming moments that naturally occur during toy play, we asked how statistical learning unfolds in real time through accumulating cross‐situational statistics in naturalistic contexts. We found that even when learning situations were individually ambiguous, learners’ performance gradually improved over time. This improvement was driven in part by learners’ use of partial knowledge acquired from previous learning situations, even when they had not yet discovered correct word‐object mappings. These results suggest that word learning is a continuous process by means of real‐time information integration. (shrink)

In recent approaches to ethics, the personal involvement of health care providers and their empathy are perceived as important elements of an overall ethical ability. Experiential working methods are used in ethics education to foster, inter alia, empathy. In 2008, the care-ethics lab ‘sTimul’ was founded in Flanders, Belgium, to provide training that focuses on improving care providers' ethical abilities through experiential working simulations. The curriculum of sTimul focuses on empathy sessions, aimed at care providers' empathic skills. The present study (...) provides better insight into how experiential learning specifically targets the empathic abilities of care providers. Providing contrasting experiences that affect the care providers' self-reflection seems a crucial element in this study. Further research is needed to provide more insight into how empathy leads to long-term changes in behaviour. (shrink)

The ongoing pandemic has transformed communication modes globally. Especially in the case of higher education, where countermeasures against coronavirus disease 2019 have affected students’ learning experience. This study emphasized the case of business simulation games, where critical factors were underlined to define learners’ intention to use an online learning environment through the lens of task technology fit as a theoretical stance. This study considered the statistical analysis of 523 students who attended the business simulation module online at the (...) tertiary level of education. Findings conclude that flow experience is the most critical factor to define learners’ perceived TTF in the case of an online learning experience. However, the learners’ self-efficacy is significant enough to map learners’ intentions to use an online environment for learning. The study discussed several theoretical and practical implications for learners’ educators and policymakers. (shrink)

In a small course on technology and society, students participated in an extended role-play simulation for two weeks. Each student played a different adult character in a fictional community, which faces technological decisions in three scenarios set in the near future. The three scenarios involved stem cell research, nanotechnology, and privacy. Each student had an active role in two scenarios and served as an observer for the third. At the beginning, students were apprehensive, excited, and uncertain. During the first and (...) second sessions, they experienced some frustration, but by the end, they were generally satisfied with the outcomes. Over the two weeks, students changed their definitions of success: Initially they tried to convince others to agree with their positions; at the end, they felt that a consensus represented success. In their final reflective essays, students reported that the role-play experience helped them learn to understand the perspectives of others. (shrink)

Analogue experiments have attracted interest for their potential to shed light on inaccessible domains. For instance, ‘dumb holes’ in fluids and Bose–Einstein condensates, as analogues of black holes, have been promoted as means of confirming the existence of Hawking radiation in real black holes. We compare analogue experiments with other cases of experiment and simulation in physics. We argue—contra recent claims in the philosophical literature—that analogue experiments are not capable of confirming the existence of particular phenomena in inaccessible target systems. (...) As they must assume the physical adequacy of the modelling framework used to describe the inaccessible target system, arguments to the conclusion that analogue experiments can yield confirmation for phenomena in those target systems, such as Hawking radiation in black holes, beg the question. (shrink)

This paper proposes a feature extraction algorithm based on the maximum entropy phrase reordering model in statistical machine translation in language learning machines. The algorithm can extract more accurate phrase reordering information, especially the feature information of reversed phrases, which solves the problem of imbalance of feature data during maximum entropy training in the original algorithm, and improves the accuracy of phrase reordering in translation. In the experiment, they were combined with linguistic features such as parts of speech, words, (...) and syntactic features extracted by using the syntax analyzer, and the maximum entropy classifier was used to predict translation errors, and the experimental verification was performed on the Chinese-English translation data set and compared. The experimental results show that different word posterior probabilities have a significant impact on the classification error rate, and the combination of linguistic features based on the word posterior probability can significantly reduce the classification error rate and improve the translation error prediction performance. (shrink)

Moral imagination is a central component of moral agency and person‐centred care. Becoming moral agents who can sustain attention on patients and their families through their illness and suffering involves imagining the other, what moral possibilities are available, what choices to make, and how one wants to be. This relationship between moral agency, moral imagination, and personhood can be effaced by a focus on task‐driven technical rationality within the multifaceted challenges of contemporary healthcare. Similarly, facilitating students' moral agency can also (...) be obscured by the task‐driven technical rationality of teaching. The development of moral agency requires deliberate attention across the trajectory of nursing education. To prepare nursing students for one practice challenge, workplace violence, we developed a multimodal education intervention which included a simulated learning experience (SLE). To enhance the realism and consistency of the educational experience, 11 nursing students were trained as simulated participants (SP). As part of a larger study to examine knowledge acquisition and practice confidence of learners who completed the SLE, we explored the experience of being the SP through interviews and a focus group with the SP students. The SP described how their multiple performances contributed to imagining the situation ‘on both sides’ prompting empathy, a reconsideration of their moral agency, and the potential to prevent violence in the workplace beyond technical rational techniques, such as verbal de‐escalation scripts. The empirical findings from the SP prompted a philosophical exploration into moral imagination. We summarise the multimodal educational intervention and relevant findings, and then, using Johnson's conception of moral imagination and relevant nursing literature, we discuss the significance of the SP embodied experiences and their professional formation. We suggest that SLEs offer a unique avenue to create pedagogical spaces which promote moral imagination, thereby teaching for moral agency and person‐centred care. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Simulation, Subjective Knowledge, and the Cognitive Value of Literary NarrativeScott R. Stroud (bio)IntroductionLiterary narrative holds the power to move individuals to thought, reflection, action, and belief. According to a longstanding view of literature, it is this impact on the reader that leads to literary narrative being valued so highly in our culture and in others. What exactly is the value of literature? Humanists such as Peter Lamarque and Stein (...) Olsen1 argue for this value in terms of perennial themes that literature allows one to "grapple with," as opposed to cognitivist accounts that discuss the value of literary narrative in terms of conveyed truths or knowledge. One particularly important position that explains the cognitive value of literature can be labeled the "Subjective Knowledge Theory" (SKT). Such an account of literature places its value in the subjective perspectives or experiences the narrative opens up to the reader. Thus, one can gain knowledge of "what it is like" to be caught in the throes of jealousy, endangered by an opposing army, or captivated by the lure of magical prowess. Lamarque and Olsen, however, argue that SKT is fundamentally flawed in its analysis of knowledge derivable from the literary narrative and in terms of its account of literary practice.I wish to defend a version of SKT in this article. In order to do so, I make and defend the following claims. First, Lamarque and Olsen's critique of SKT relies on a conflation of two distinct types of knowledge—the knowledge provided by the simulated subjective experience and its appropriation/ generalization to forms useful for the reader's real life activities. I will argue that the former of these outcomes is due strictly to the aesthetic features of the literary narrative, whereas the second involves a non-necessary psychological reaction to the text (that is, judgments of the veracity or usefulness of the text for one's own purposes). By conflating both of these into the cognitive knowledge derivable from the text, Lamarque and Olsen's critique can [End Page 19] gain its purchase against SKT. If these two processes and the resultant sorts of knowledge are separated, then the SKT account does seem to show how literature holds value in itself and in relation to the reader's moral activities/ judgments. Second, the process of simulation is the primary means by which one can gain any type of subjective knowledge from a literary narrative. This type of knowledge will be gained by virtue of the literary narrative's aesthetic qualities, which result in a certain type of activity in the reader. Third, I will argue that the second sort of knowledge—that derived from the simulated subjective experience—results from the process of reader identification with the values, beliefs, and/or behaviors of the simulated agent. This sense of identification involves selective appropriation and generalization and will be shown not to be subject to the critiques of simple identification offered by Noël Carroll.2 It is at this stage that individuals learn what they believe they ought to value, how they ought to act, and what they should believe from their experience of simulation in reading the literary narrative. Notice that this knowledge is separate from the first sort of knowledge, which is knowledge of what it is like to experience x through y's eyes.As I elucidate and defend these claims, I hope it will become clear that this is an account that does justice to the value resident in literature and in the activities readers do after they partake in the aesthetic object of the literary narrative. Thus, I will conclude by showing how this account does not fall prey to the conflation that both critics and supporters of SKT commit in muddling the different types of knowledge available from and in relation to a literary narrative.Before I proceed, it is important that some basic concepts are clearly set forth. A narrative can be defined as any representation of two or more events over time. The number of events and the relationship among them can be as simple or complex as one likes, but the crucial aspect is that the representation supplies the... (shrink)

In typical statistical learning studies, researchers define sequences in terms of the probability of the next item in the sequence given the current item (or items), and they show that high probability sequences are treated as more familiar than low probability sequences. Existing accounts of these phenomena all assume that participants represent statistical regularities more or less as they are defined by the experimenters—as sequential probabilities of symbols in a string. Here we offer an alternative, or possibly supplementary, hypothesis. (...) Specifically, rather than identifying or labeling individual stimuli discretely in order to predict the next item in a sequence, we need only assume that the participant is able to represent the stimuli as evincing particular similarity relations to one another, with sequences represented as trajectories through this similarity space. We present experiments in which this hypothesis makes sharply different predictions from hypotheses based on the assumption that sequences are learned over discrete, labeled stimuli. We also present a series of simulation models that encode stimuli as positions in a continuous two‐dimensional space, and predict the next location from the current location. Although no model captures all of the data presented here, the results of three critical experiments are more consistent with the view that participants represent trajectories through similarity space rather than sequences of discrete labels under particular conditions. (shrink)

Simulation software used for modeling has become as ubiquitous as computers themselves. Despite growing reliance on simulation in educational and workplace settings, users encounter frustration in using simulation software programs. The authors conducted a study with 26 engineering students and interviewed them about their experience learning the simulation software Arena for optimization modeling. These students experienced frustration with the process of learning to “think” like the simulation software. Students explained their difficulty with learning the software in a (...) way that implied human dialogue with a machine and negotiation with Arena in an attempt to overcome this frustration. Rather than being gender specific, frustrations were experienced by most male and female students equally, specifically those who held a perception of difference between human and machine “thinking.” The authors contend that communication difficulty with the embedded assumptions of the software is the source of frustration rather than deficiencies of users. (shrink)

In order to explore the correlation between students’ seat choice and interaction preference in the open gamification scenario, an experiment has been carried out on the platform of provincial virtual simulation experiment teaching center of a university, and tested the relationship between absolute distance, seat type, workstation type, and students’ interaction preference. The results show that in the virtual-reality fusion gamification scenario where students can move freely: The inner circle students can stimulate the outer circle students’ willingness to invest in (...) learning. The task attribute and the seat distribution of the group may lead to the difference of students’ interaction preference. Students are more likely to learn knowledge and skills by interacting with “people” rather than “object.” Gender and major influence students’ experience of participating in gamified teaching. The results confirm that the interactive engagement effect of location does exist in immersive virtual-reality fusion gamification teaching scenario, and suggestions are put forward to adjust the effect of location through instructional design and teacher intervention. (shrink)

I present a game-theoretical multi-agent system to simulate the evolutionary process responsible for the pragmatic phenomenon division of pragmatic labour (DOPL), a linguistic convention emerging from evolutionary forces. Each agent is positioned on a toroid lattice and communicates via signaling games , where the choice of an interlocutor depends on the Manhattan distance between them. In this framework I compare two learning dynamics: reinforcement learning (RL) and belief learning (BL). An agent’s experiences from previous plays influence (...) his communication behaviour, and RL agents act in a non-rational way whereas BL agents display a small degree of rationality by using best response dynamics . The complete system simulates an evolutionary process of communication strategies, which agents can learn in a structured spatial society. The significant questions are: what circumstances could lead to an evolutionary process that doesn’t result in the expected DOPL convention; and to what extent is interlocutor rationality necessary for the emergence of a society-wide convention à la DOPL? (shrink)

Prior research has used an Interactive Landslide Simulator tool to investigate human decision making against landslide risks. It has been found that repeated feedback in the ILS tool about damages due to landslides causes an improvement in human decisions against landslide risks. However, little is known on how theories of learning from feedback would account for human decisions in the ILS tool. The primary goal of this paper is to account for human decisions in the ILS tool via computational (...) models based upon reinforcement learning and to explore the model mechanisms involved when people make decisions in the ILS tool. Four different reinforcement-learning models were developed and evaluated in their ability to capture human decisions in an experiment involving two conditions in the ILS tool. The parameters of an Expectancy-Valence model, two Prospect-Valence-Learning models, a combination EV-PU model, and a random model were calibrated to human decisions in the ILS tool across the two conditions. Later, different models with their calibrated parameters were generalized to data collected in an experiment involving a new condition in ILS. When generalized to this new condition, the PVL-2 model’s parameters of both damage-feedback conditions outperformed all other RL models. We highlight the implications of our results for decision making against landslide risks. (shrink)

The article considers a pressing problem in the field of inclusive education: creating a comfortable learning environment for the effective education of children with special needs. In this article, a mobile electronic alphabet Braille simulator is an element of the learning environment for children with special needs. The article describes an experiment on teaching visually impaired and blind children using a mobile electronic Braille alphabet simulator. The mobile electronic Braille alphabet trainer, based on new advanced technology, was developed (...) by Kazakh scientist-inventor Galimzhan Gabdreshov under the brand of his company SEZUAL. It was developed to reduce the time that blind children need to learn to read. The relevance of the study lies in the need to educate visually impaired and blind children through the introduction of modern technologies. Children entering primary, mainstream and special needs schools have been learning Braille for several years with varying degrees of success. The article shows the result of an experiment on teaching children using an electronic Braille alphabet simulator and without this simulator. The experiment showed the benefits of teaching blind children using a Braille simulator. An experimental study on the implementation of the SEZUAL electronic alphabet simulator with Braille was carried out in schools for the blind in the cities of Atyrau and Astana. A way to improve a mobile electronic alphabet Braille simulator is to make a simultaneous sound signal when a child presses the keys of the Braille simulator, with different Braille characters. To enhance the impact on the associative zone of the cerebral cortex, in the Braille simulator, sound signals of each key are added to the touch keys, which, like visual signals, are processed by the associative zone of the cerebral cortex and help to consolidate the perception of the simulator keys. This article describes in detail an experiment on the assimilation of educational material by blind and visually impaired children using a combination of parameters of sensorimotor and auditory perception of children. To clarify the peculiarities of the perception of blind and visually impaired respondents, their leading representative systems and modalities were identified before the experiment. The test was conducted based on the educational institution Atyrau Regional School for Gifted Children, Republic of Kazakhstan. (shrink)

In this paper, various dimensions of care involved in mathematics education are linked to the need to develop classroom activities that connect mathematics and social justice issues. Drawing from literature that shows cognition is situated and embodied, the importance of meaningful contextualization and social interaction when learning mathematics is highlighted. The concept of “simulation-based mathematics and social justice activities” is presented as an approach for the work of bringing social justice issues that have mathematics at their core to the (...) classroom. Theoretical constructs and examples are discussed, to illustrate what such simulations may entail and what may be learned from scholars, in different educational fields, who use simulations in classroom activities. Potentially beneficial features of social justice simulations are related to various educational goals, such as: decreasing arbitrary boundaries between mathematical sub-areas and between mathematics and other disciplines; providing opportunities for choice and the embodiment of different perspectives; and offering opportunities for inter-personal learning. I report on a simulation-based mathematics and social justice activity, conducted in a teacher education classroom. Students—in this case future teachers—were prompted to write reflectively about their participation in the activity. My interest lies in finding out what, if any, cognitive and affective benefits these prospective teachers connect with their experience of mathematics in the activity. To investigate this, I analyze six themes that are present in the data and illustrate each theme using excerpts of student writing. The thematic analysis allows us to learn about connections made by these students, between mathematics, in the context of the activity, and issues that are personally meaningful to them, such as: their own future teaching practice, learning and interacting with peers, beliefs and feelings about mathematics and the learning of mathematics, and different perspectives on complex decisions, involving cooperation or lack thereof, that are encountered in real life situations. (shrink)

Teaching the nuances of ethical decision making is particularly challenging in fully online, asynchronous courses where real-time discussion is not an option. Digital simulations, in the context of an integrative online ethics course, can offer applied learning and assessment experiences. However, scholarship on the impact of digital simulations for teaching ethical decision making is limited. The purpose of this study is to explore whether digital simulation used as an assessment for ethical reasoning and complex decision making is effective (...) in helping business students heighten their awareness of values in tension and discern ethical paths to resolution. We conduct an exploratory analysis of two ethics simulations used in teaching nine graduate business ethics classes offered in an asynchronous, online format. We discuss the results in terms of the Markkula Center for Applied Ethics’ five-step ethical decision making framework and outline implications for teaching and future research on business ethics simulations. (shrink)

The systemic complexity of sustainable development imposes a major cognitive challenge to students’ learning. Faculty can explore new approaches in the classroom to teach the topic successfully, including the use of technology. We conducted an experiment to compare the effectiveness of a simulation vis-à-vis a case-based method to teach sustainable development. We found that both pedagogical methods are effective for teaching this concept, although our results support the idea that simulations are slightly more effective than case studies, particularly to (...) teach its multidimensional and inter-temporal nature. Therefore, our findings suggest the use of both simulations and case studies as pedagogical tools to convey the main ideas associated with sustainable development. (shrink)

This article presents a sociomaterial account of simulation in higher education. Sociomaterial approaches change the ontological and epistemological bases for understanding learning and offer valuable tools for addressing important questions about relationships between university education and professional practices. Simulation has grown in many disciplines as a means to bring the two closer together. However, the theoretical underpinnings of simulation pedagogy are limited. This paper extends the wider work of applying sociomaterial approaches to educational phenomena, taking up Schatzki’s practice theory (...) as a distinctive basis for doing so. The question ‘What is being simulated?’ is posed, prompting discussion of multiple bodies, performances and experiences. The potential of adopting such a framework for understanding simulation as a pedagogic practice that brings the classroom and workplace together is illustrated with reference to clinical education in nursing. (shrink)

This article addresses the ability of Parallel Distributed Processing (PDP) networks to generate stagewise cognitive development in accordance with Piaget's theory of cognitive epigenesis. We carried out a replication study of the simulation experiments by McClelland (1989) and McClelland and Jenkins (1991) in which a PDP network learns to solve balance scale problems. In objective tests motivated from catastrophe theory, a mathematical theory of transitions in epigenetical systems, no evidence for stage transitions in network performance was found. It is concluded (...) that PDP networks lack the ability to recover the positive outcomes of analogous catastrophe analyses of real cognitive developmental data. In an attempt to further characterize the learning behaviour of PDP networks, we carried out a second simulation study using the discrimination‐shift paradigm. The results thus obtained indicate that PDP learning is compatible with the learning of stimulus‐response relationships, not with the acquisition of mediating rules such as conceived in (neo‐)Piagetian theory. In closing, we speculate about the feasibility of simulating stagewise development with alternative network architectures. (shrink)

The question of whether studies of human learning provide evidence for distinct conscious and unconscious influences remains as controversial today as ever. Much of this controversy arises from the use of the logic of dissociation. The controversy has prompted the use of an alternative approach that places conscious and unconscious influences on memory retrieval in opposition. Here we ask whether evidence acquired via the logic of opposition requires a dual-process account or whether it can be accommodated within a single (...) similarity-based account. We report simulations using a simple neural network model of two artificial grammar learning experiments reported by Higham, Vokey, and Pritchard that dissociated conscious and unconscious influences on classification. The simulations demonstrate that opposition logic is insufficient to distinguish between single- and multiple-system models. (shrink)

The article covers the simulation approach as a part of communicative-oriented teaching, where its main task is to remove psychological barriers in education leading to the fast and effective language learning. The main aim of this method is to provide a life experience through the modern educational environment. Modeling creates situations which helps us to try other strategies while sinking into screenplay. An example in the article we consider a linguo-didactic resource "Время говорить по-русски". The research relevant is vivid: (...) the traditional forms of education are being replaced by the modern technologies. (shrink)

Learning in natural environments is often characterized by a degree of inconsistency from an input. These inconsistencies occur, for example, when learning from more than one source, or when the presence of environmental noise distorts incoming information; as a result, the task faced by the learner becomes ambiguous. In this study, we investigate how learners handle such situations. We focus on the setting where a learner receives and processes a sequence of utterances to master associations between objects and (...) their labels, where the source is inconsistent by design: It uses both “correct” and “incorrect” object‐label pairings. We hypothesize that depending on the order of presentation, the result of the learning may be different. To this end, we consider two types of symbolic learning procedures: the Object‐Label (OL) and the Label‐Object (LO) process. In the OL process, the learner is first exposed to the object, and then the label. In the LO process, this order is reversed. We perform experiments with human subjects, and also construct a computational model that is based on a nonlinear stochastic reinforcement learning algorithm. It is observed experimentally that OL learners are generally better at processing inconsistent input compared to LO learners. We show that the patterns observed in the learning experiments can be reproduced in the simulations if the model includes (a) an ability to regularize the input (and also to do the opposite, i.e., undermatch) and (b) an ability to take account of implicit negative evidence (i.e., interactions among different objects/labels). The model suggests that while both types of learners utilize implicit negative evidence in a similar way, there is a difference in regularization patterns: OL learners regularize the input, whereas LO learners undermatch. As a result, OL learners are able to form a more consistent system of image‐utterance associations, despite the ambiguous learning task. (shrink)

The study aims to explore the roles of Massive Open Online Courses based on deep learning in college students’ English grammar teaching. The data are collected using a survey. After the experimental data are analyzed, it is found that students have a low sense of happiness and satisfaction and are unwilling to practice oral English and learn language points in English learning. They think that college English learning only meets the needs of CET-4 and CET-6 and does (...) not take it as the ultimate learning goal. After the necessity and problems in English grammar teaching are discussed, the advantages of flipped classrooms of MOOCs are discussed in English grammar teaching. A teaching platform is constructed to study the foreign language teaching mode under MOOCs, and classroom teaching is combined with the advantages of MOOCs following the principle of “teaching students according to their personalities” to improve the listening, speaking, reading, writing, and translation skills of foreign language majors. The results show that high-quality online teaching resources and the deep learning-based teaching environment can provide a variety of interactive tools, by which students can communicate with their peers and teachers online. Sharing open online communication, classroom discussion, and situational simulation can enhance teachers’ deep learning ability, like the ability to communication and transfer thoughts. Constructivism with interaction as the core can help students grasp new knowledge easily. Extensive communication and interaction are important ways for learning and thinking. The new model provides students with profound learning experience, expands the teaching resources of MOOCs around the world, and maximizes the interaction between online and offline teachers and students, making knowledge widely rooted in the campus and realizing the combination of online resources and campus classroom teaching. Students can learn the knowledge through autonomous learning and discussion before class, which greatly broadens the learning time and space. In the classroom and after class, the internalization and sublimation of knowledge are completed through group cooperation, inquiry learning, scenario simulation, display, and evaluation, promoting students to know about new knowledge and highlighting the dominant position of students. (shrink)

The journey into the world of midwifery or nursing requires the student to attend to the intertwining of self-body-world in order to shift their knowledge of self-body-world into a client/patient-centered context. One of the teaching-learning strategies used to provide safe opportunities is the use of simulations and virtual practices. Rather than learning intimate acts of touching, or life and death decision-making in situations with actual clients/patients, students enter their learning world with rubber torsos, cloth babies, and cyber (...) clinics. The “other” is a simulated other, not a human. How does the student shift from seeing this simulated other as object to a sense of other as subject? In our world of constant use of technology for communication and entertainment, do students shift in and out of a cyber world easily or are they more captured by the simulated experience than with the human world? Has the human world redefined itself where the intertwining of self-body-world blurs the sense of where human body ends and cyber or simulated world begins? What is the place of Bildung when engaged with a cyber other? As a result of educational challenges, including rising enrolments, limited clinical placement opportunities, and increasing risk management concerns, there has been a proliferation in the use of simulation as a teaching strategy. This has left us –the authors– wondering about the student experience of simulation. What do they learn? How do they learn? How can this learning be applied in practice? (shrink)

Quantum computing is of high interest because it promises to perform at least some kinds of computations much faster than classical computers. Arute et al. 2019 (informally, “the Google Quantum Team”) report the results of experiments that purport to demonstrate “quantum supremacy” – the claim that the performance of some quantum computers is better than that of classical computers on some problems. Do these results close the debate over quantum supremacy? We argue that they do not. In the following, we (...) provide an overview of the Google Quantum Team’s experiments, then identify some open questions in the quest to demonstrate quantum supremacy. (shrink)

This article addresses the ability of Parallel Distributed Processing (PDP) networks to generate stagewise cognitive development in accordance with Piaget's theory of cognitive epigenesis. We carried out a replication study of the simulation experiments by McClelland (1989) and McClelland and Jenkins (1991) in which a PDP network learns to solve balance scale problems. In objective tests motivated from catastrophe theory, a mathematical theory of transitions in epigenetical systems, no evidence for stage transitions in network performance was found. It is concluded (...) that PDP networks lack the ability to recover the positive outcomes of analogous catastrophe analyses of real cognitive developmental data. In an attempt to further characterize the learning behaviour of PDP networks, we carried out a second simulation study using the discrimination‐shift paradigm. The results thus obtained indicate that PDP learning is compatible with the learning of stimulus‐response relationships, not with the acquisition of mediating rules such as conceived in (neo‐)Piagetian theory. In closing, we speculate about the feasibility of simulating stagewise development with alternative network architectures. (shrink)

This article addresses the ability of Parallel Distributed Processing (PDP) networks to generate stagewise cognitive development in accordance with Piaget's theory of cognitive epigenesis. We carried out a replication study of the simulation experiments by McClelland (1989) and McClelland and Jenkins (1991) in which a PDP network learns to solve balance scale problems. In objective tests motivated from catastrophe theory, a mathematical theory of transitions in epigenetical systems, no evidence for stage transitions in network performance was found. It is concluded (...) that PDP networks lack the ability to recover the positive outcomes of analogous catastrophe analyses of real cognitive developmental data. In an attempt to further characterize the learning behaviour of PDP networks, we carried out a second simulation study using the discrimination‐shift paradigm. The results thus obtained indicate that PDP learning is compatible with the learning of stimulus‐response relationships, not with the acquisition of mediating rules such as conceived in (neo‐)Piagetian theory. In closing, we speculate about the feasibility of simulating stagewise development with alternative network architectures. (shrink)

Cognitively-oriented theories have dominated the recent history of the study of emotion. However, critics of this perspective suggest the role of the body in the experience of emotion is largely ignored by cognitive theorists. As an alternative to the cognitive perspective, critics are increasingly pointing to William James’ theory, which emphasized somatic aspects of emotions. This emerging emphasis on the embodiment of emotions is shared by those in the field of AI attempting to model human emotions. Behavior-based agents in AI (...) are attempts to model the role the body might play in the experiencing of emotions. Progress in creating such behavior-based models that function in their environments has been slow, suggesting some potential problems with Jamesian alternatives to cognitive perspectives of emotions. Heidegger’s and Merleau-Ponty’s conceptions of embodiment are suggested as alternatives to James’ and as means for addressing the shortcomings of the cognitive perspective. (shrink)

To generate empathy in the care of vulnerable older persons requires care providers to reflect critically on their care practices. Ethics education and training must provide them with tools to accomplish such critical reflection. It must also create a pedagogical context in which good care can be taught and cultivated. The care-ethics lab ‘sTimul’ originated in 2008 in Flanders with the stimulation of ethical reflection in care providers and care providers in training as its main goal. Also in 2008, sTimul (...) commenced the organization of empathy sessions as an attempt to achieve this goal by simulation. The empathy session is a practical and fairly straightforward way of working to provoke care providers and care providers in training to engage in ethical reflection. Characteristic of the empathy session in the care-ethics lab is the emphasis on experience as a basis for ethical reflection. (shrink)

A deep reinforcement learning-based computational guidance method is presented, which is used to identify and resolve the problem of collision avoidance for a variable number of fixed-wing UAVs in limited airspace. The cooperative guidance process is first analyzed for multiple aircraft by formulating flight scenarios using multiagent Markov game theory and solving it by machine learning algorithm. Furthermore, a self-learning framework is established by using the actor-critic model, which is proposed to train collision avoidance decision-making neural networks. (...) To achieve higher scalability, the neural network is customized to incorporate long short-term memory networks, and a coordination strategy is given. Additionally, a simulator suitable for multiagent high-density route scene is designed for validation, in which all UAVs run the proposed algorithm onboard. Simulated experiment results from several case studies show that the real-time guidance algorithm can reduce the collision probability of multiple UAVs in flight effectively even with a large number of aircraft. (shrink)

Background Although simulation-based learning using simulated patients is a standard part of training in medical school, it is not yet used to the same extent in the teaching of medical ethics. There are good reasons to use simulation-based teaching, especially in clinical ethics, to gain practical experience through the situation-specific combination of knowledge, skills, and attitudes in the learning process. However, there are certain prerequisites regarding the design of simulations with actors in medical ethics education. Topics Using (...) a concrete example, this article aims to provide an overview of the development and conception of simulation and role scripts for simulations with actors to teach clinical ethics, which is an important subfield of medical ethics. The special requirements and specifics of these simulations are addressed. Conclusion Although there are some limitations with regard to integrating simulations into clinical ethics, simulation-based training of knowledge, skills, and attitudes can and should play a role in medical–ethical theory and clinical–ethical practice, not only for medical and nursing students but also in the further training of clinical ethicists. (shrink)

Critical pedagogy, by brealdng down the boundaries between the academy and society, creates opportunities for deep and transformative learning. Inspired by bell hooks' call to engage the hearts as well as the minds of learners, this essay demonstrates two teaching methods that engage college students in intellectual inquiry that potentially challenges and undermines societal power relations. The first literally broadens the walls of the classroom through community-based projects. The second constructs an in-class learning experience that cultivates inter-personal perspective (...) taking by simulating arbitrary and systemic inequality. Both approaches inherently question received relationships of power, within and outside of the classroom, by creating opportunities for learners to transgress the boundaries imposed by individual experience, enabling them to envision connections across social and economic difference. Through active learning experiences that connect affective responses to new learning, students gain insight into the ways systems of domination construct social privilege and structural oppression. Urging all of us to open our minds and hearts so that we can know beyond the boundaries of what is acceptable, so that we can think and rethink, so that we can create new visions, I celebrate teaching that enables transgressions—a movement against and beyond boundaries. It is that movement which makes education the practice of freedom. bell hooks, Teaching to Transgress (1994: 12). (shrink)

Symbols enable people to organize and communicate about the world. However, the ways in which symbolic knowledge is learned and then represented in the mind are poorly understood. We present a formal analysis of symbolic learning—in particular, word learning—in terms of prediction and cue competition, and we consider two possible ways in which symbols might be learned: by learning to predict a label from the features of objects and events in the world, and by learning to (...) predict features from a label. This analysis predicts significant differences in symbolic learning depending on the sequencing of objects and labels. We report a computational simulation and two human experiments that confirm these differences, revealing the existence of Feature-Label-Ordering effects in learning. Discrimination learning is facilitated when objects predict labels, but not when labels predict objects. Our results and analysis suggest that the semantic categories people use to understand and communicate about the world can only be learned if labels are predicted from objects. We discuss the implications of this for our understanding of the nature of language and symbolic thought, and in particular, for theories of reference. (shrink)

The conscious experiences we have during sleep have the potential to improve our empathetic response to those who experience delusions and psychosis by supplying a virtual reality simulation of mental illness. Empathy for those with mental illness is lacking and there has been little improvement in the last decades despite efforts made to increase awareness. Our lack of empathy, in this case, may be due to an inability to accurately mentally simulate what it’s like to have a particular cognitive (...) disorder. Dreaming can help mitigate these deficits by placing the dreamer directly into a realistic virtual simulation and thus increase their capacity for empathy. Increasing empathy would go some way towards reducing the stigma and discrimination faced by people in this group. Recent work suggests that virtual reality can increase empathy towards a variety of marginalised groups, however, this technology is limited in its ability to simulate mental illnesses such as delusions. Dreams, however, are at times virtual reality delusion simulators. They can replicate, to a reasonable degree, delusions and psychosis, and through these experiences, we can learn ‘what it’s like’ to have these conditions. It is essential that we recognise these experiences for what they are, attempt to remember and reflect on them. Instead of disregarding dreams due to their unusualness and bizarreness, we can learn from these experiences and expand our understanding of the human condition and its many forms. (shrink)

By reviewing most of the neurobiology of consciousness, this article highlights some major reasons why a successful emulation of the dynamics of human consciousness by artificial intelligence is unlikely. The analysis provided leads to conclude that human consciousness is epigenetically determined and experience and context-dependent at the individual level. It is subject to changes in time that are essentially unpredictable. If cracking the code to human consciousness were possible, the result would most likely have to consist of a temporal pattern (...) code simulating long-distance signal reverberation and de-correlation of all spatial signal contents from temporal signals. In the light of the massive evidence for complex interactions between implicit (non-conscious) and explicit (conscious) contents of representation, the code would have to be capable of making implicit (non-conscious) processes explicit. It would have to be capable of a progressively less and less arbitrary selection of temporal activity patterns in a continuously developing neural network structure identical to that of the human brain, from the synaptic level to that of higher cognitive functions. The code’s activation thresholds would depend on specific temporal signal coincidence probabilities, vary considerably with time and across individual experience data, and would therefore require dynamically adaptive computations capable of emulating the properties of individual human experience. No known machine or neural network learning approach has such potential. (shrink)

Over the past decade, sequence learning has gradually become a central paradigm through which to study implicit learning. In this chapter, we start by briefly summarizing the results obtained with different variants of the sequence learning paradigm. We distinguish three subparadigms in terms of whether the stimulus material is generated either by following a fixed and repeating sequence (e.g., Nissen & Bullemer, 1987), by relying on a complex set of rules from which one can produce several alternative (...) deterministic sequences (e.g., Lewicki, Hill & Bizot, 1988; Stadler, 1989), or by following the output of a probabilistic set of rules such as instantiated by noisy finite-state grammars (Cleeremans & McClelland, 1991; Jiménez, Mendéz & Cleeremans, 1996). Next, we focus on the processes involved in sequence representation and acquisition. We suggest that the sensitivity to the sequential structure observed in the probabilistic subparadigm can only be a result of the acquisition of a representation of the statistical constraints of the material, and that this sensitivity emerges through the operation of mechanisms that are well instantiated by connectionist models such as the Simple Recurrent Network (Elman, 1990; Cleeremans, 1993b). We present new simulation work meant to explore to what extent the model can also account for specific data obtained in a paradigmatic instance of deterministic, rule-based sequence learning task: Lewicki et al. (1988)'s situation. Finally, we report on the results of an experiment that compares learning on otherwise similar deterministic and probabilistic structures, and we show that learning of both types of structures is equivalent only under conditions that maximally hinder explicit acquisition. Taken together, these simulation and experimental data lend support to the claim that implicit learning in all three sequence learning subparadigms can amount to a form of statistical sequence learning. They also suggest that distinguishing among several theories of sequence representation and acquisition may require us to analize the data in great detail. Hopefully, however, some truth can be found in such details.. (shrink)

This paper focuses on neural learning from adaptive neural control for a class of flexible joint manipulator under the output tracking constraint. To facilitate the design, a new transformed function is introduced to convert the constrained tracking error into unconstrained error variable. Then, a novel adaptive neural dynamic surface control scheme is proposed by combining the neural universal approximation. The proposed control scheme not only decreases the dimension of neural inputs but also reduces the number of neural approximators. Moreover, (...) it can be verified that all the closed-loop signals are uniformly ultimately bounded and the constrained tracking error converges to a small neighborhood around zero in a finite time. Particularly, the reduction of the number of neural input variables simplifies the verification of persistent excitation condition for neural networks. Subsequently, the proposed ANC scheme is verified recursively to be capable of acquiring and storing knowledge of unknown system dynamics in constant neural weights. By reusing the stored knowledge, a neural learning controller is developed for better control performance. Simulation results on a single-link flexible joint manipulator and experiment results on Baxter robot are given to illustrate the effectiveness of the proposed scheme. (shrink)

This exploration aims to study the emotion recognition of speech and graphic visualization of expressions of learners under the intelligent learning environment of the Internet. After comparing the performance of several neural network algorithms related to deep learning, an improved convolution neural network-Bi-directional Long Short-Term Memory algorithm is proposed, and a simulation experiment is conducted to verify the performance of this algorithm. The experimental results indicate that the Accuracy of CNN-BiLSTM algorithm reported here reaches 98.75%, which is at (...) least 3.15% higher than that of other algorithms. Besides, the Recall is at least 7.13% higher than that of other algorithms, and the recognition rate is not less than 90%. Evidently, the improved CNN-BiLSTM algorithm can achieve good recognition results, and provide significant experimental reference for research on learners’ emotion recognition and graphic visualization of expressions in an intelligent learning environment. (shrink)

Since 2008, in Flanders, we organize immersion sessions in a simulated context with the aim of stimulating student nurses and health professionals to learn virtuous caring. In this contribution, we first outline the purpose of this experiential learning: the cultivation of moral character. We come to the core of what we mean by moral character for care. We refer to Joan Tronto and Stan van Hooft to claim that caring is central to all aspects of nursing practice and (...) is the basis of its moral quality. We also stipulate that caring involves the integration of action with emotions, motivations, and knowledge. Second, we briefly explain how the immersion sessions in the care ethics lab take place and, in particular, reflect on what it yields in terms of experiences for the participants who take on the role of simulant patients in this experiential learning process. We focus on the significant role contrast experiences play in these experiences. Especially the negative contrast experiences do not wear off easily; care professionals remember even long after the immersion session and continue to carry them with them as a “corporeal built-in alarm.” Third, we discuss the role of contrast experiences in cultivating moral character for care. In particular, we explore the role of the body in the kind of knowing it cultivates and, by extension, its role in cultivating virtuous caring. By referring to specific philosophical ideas of Gabriël Marcel, Hans Jonas and Emmanuel Levinas, we try to understand how contrast experiences bring about an integration of virtuous action into knowledge, motivation, and emotion. We conclude that we need more space for contrast experiences in cultivating moral character. More attention should be paid to the role of the body in this learning process. (shrink)

Evidence presented in Salmon (2001; Econometrica 69(6) 1597) indicates that typical tests to identify learning behavior in experiments involving normal form games possess little power to reject incorrect models. This paper begins by presenting results from an experiment designed to gather alternative data to overcome this problem. The results from these experiments indicate support for a learning-to-learn or rule learning hypothesis in which subjects change their decision rule over time. These results are then used to construct an (...) adaptive learning model which is intended to mimic more accurately the behavior observed. The final section of the paper presents results from a simple simulation based analysis comparing the performance of this adaptive learning model with that of several standard decision rules in reproducing the choice patterns observed in the experiment. (shrink)